Wireless Local Area Network (WLAN) equipment, such as clients and Access Points (APs), operate in an environment where the APs are fixed in location, but the client devices may move about from place to place. Mobile client devices typically move from the coverage area of one AP to another, a function referred to as roaming. As a client moves away from an AP, the signal strength (and thus the signal quality) of its link to that AP decreases. If the distance becomes great enough, the client can no longer transfer data to that AP; the client must find a closer AP and connect to such closer AP. This process of disconnecting from one AP and reconnecting to another AP requires a significant amount of processing power, and often involves a substantial delay and possible loss of data. It is therefore of interest to quantify the mobility performance of WLAN devices, in terms of the amount of time required to roam between APs, and the wireless data lost thereby.
Further, if a large number of clients are simultaneously roaming within a WLAN system, a heavy load can result. For example, a WLAN system may be able to support the mobility of a single client, but may fail to adequately support the mobility of 100 clients. It is therefore of interest to quantify the mobility performance of WLAN devices in terms of the number of simultaneously roaming devices that can be supported.
Further, if many clients continue to roam for a long duration of time, a significant number of state changes may take place within the WLAN system. This in turn may cause stability or performance problems in the WLAN equipment. It is therefore of interest to quantify the mobility performance of WLAN devices in terms of the duration of time for which roaming can be carried out without problems.
Further, the process of disconnecting a client from one AP and reconnecting to another AP involves co-operative protocol transactions that must be supported by both the client and the two APs. If either the client or the AP fails to properly implement these protocol transactions, then the mobility performance of the entire WLAN system may be adversely affected. However, it is necessary to distinguish those performance issues that may be induced by clients, from those performance issues that may be induced by APs. It is therefore of interest to separately quantify the mobility performance of client devices and APs.
Heretofore, the measurement of the mobility performance of WLAN equipment has been performed by setting up three or more actual WLAN devices, at least one of which is a client device and at least two of which are AP devices; causing the WLAN client device or devices to roam between the AP devices; and then measuring mobility performance according to the desired metric.
One approach that has been implemented to date to carry out mobility performance measurements consists of placing real WLAN equipment (both real clients and real APs) within a large physical space, and then physically moving the devices in order to increase or decrease the distance between them. The mobility performance metrics may be quantified by observing the behavior of the WLAN clients and APs as the relative distances between them change. Unfortunately, this method requires a large floor space, is highly labor-intensive, subject to variations due to human error, and is prone to interference and external signals. Further, it is neither cost-effective nor repeatable. Still further, it is very difficult to predict or control the points in time when different clients may elect to roam, which renders the measurement process inaccurate, or otherwise error-prone.
Another approach that has been implemented to date consists of placing real WLAN equipment (again, real clients and real APs) into separate shielded chambers that are interconnected using variable RF attenuators. Increasing the amount of attenuation interposed between an AP and a client simulates an increase of distance between them. Conversely, decreasing the amount of attenuation simulates a decreasing distance between them. Therefore, by increasing the amount of attenuation between a client and a first AP, and simultaneously decreasing the amount of attenuation between the same client and a second AP, the client may be caused to roam from the first AP to the second AP. Mobility performance metrics may be quantified when the client roams. This approach avoids some of the problems of the first mentioned method. It can be automated, eliminates the issues of interference, and affords some degree of control of the point at which the actual roaming takes place. Nevertheless, it too suffers from severe limitations. The roaming sequences that may be implemented are highly constrained, due to the use of fixed physical topologies of attenuators to define the movement of clients; many roaming patterns cannot be emulated, or otherwise created, without being adversely impacted by RF coupling and leakage issues. The test setup is expensive and bulky, and does not scale to large numbers of clients and APs. Further, the approach suffers from unpredictable variations due to the manufacturing tolerances of the client and AP radio transceivers. Still further, such approach relies on the use of both clients and APs in the same test; as a consequence, the mobility performance of the clients cannot be separated from that of the APs, and the only measurements that can be made are relative ones, i.e., the performance of a specific client in conjunction with a specific AP.